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Fluocell for Ratiometric and High-Throughput Live-Cell Image Visualization and Quantitation.

Qin Qin1, Shannon Laub1, Yiwen Shi2

  • 1Department of Bioengineering, Institute of Engineering in Medicine, University of California, San Diego, San Diego, CA, United States.

Frontiers in Physics
|November 9, 2020
PubMed
Summary

Fluocell is a new open-source software for visualizing and quantifying live-cell fluorescent ratio images. It enables high-throughput, subcellular analysis of molecular dynamics, aiding in understanding cellular functions.

Keywords:
high-throughputimage analysislive-cell imagequantitationratiometricvisualization

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Area of Science:

  • Cellular and Molecular Biology
  • Biophysics
  • Software Development for Life Sciences

Background:

  • Spatiotemporal regulation of molecular activities is crucial for cellular function and fate.
  • Analyzing dynamic molecular activities in live cells requires high-throughput visualization and quantitation of fluorescent ratio images with subcellular resolution.
  • Existing software tools often lack the specific capabilities for advanced ratiometric live-cell imaging analysis.

Purpose of the Study:

  • To introduce Fluocell, an open-source software package designed for visualizing and quantifying pixelwise ratiometric images from live cells.
  • To provide tools for calculating ratio time courses, performing group statistics, kinetic analysis, and 3D visualization of ratio images.
  • To demonstrate Fluocell's utility in analyzing Förster (or fluorescence) resonance energy transfer (FRET)-based biosensor data for high-throughput, single-cell dynamic analysis.

Main Methods:

  • Development and characterization of the open-source Fluocell software package.
  • Utilization of Fluocell for ratiometric analysis of intensity images from FRET-based biosensors.
  • Application of Fluocell to visualize and quantify dynamic molecular activities in heterogeneous populations of single live cells.
  • Analysis of spatiotemporal data, including Fyn kinase activation kinetics and epigenetic signals in mitotic cells.

Main Results:

  • Fluocell enables visualization and quantitation of pixelwise ratiometric images with subcellular resolution and high throughput.
  • The software facilitates group statistics, kinetic analysis, and 3D visualization of ratio images.
  • Demonstrated distinct activation kinetics of Fyn kinase in different cellular compartments.
  • Visualized 4D spatiotemporal distribution of epigenetic signals in mitotic cells.

Conclusions:

  • Fluocell offers an integrated environment for ratiometric live-cell image visualization and analysis.
  • The software generates high-quality single-cell dynamic data essential for quantitative modeling.
  • Fluocell supports the machine-learning of biophysical and biochemical computational models for cellular molecular regulations.